The dataset below was collected from a survey to determine whether CFT development in the island can be used as a strategy for the sustainable management and utilization of the fishery and aquatic resources in small islands. It shows the monthly income (in thousand pesos) estimated by 200 randomly selected fishers in Guimaras according to the type of fishers (i.e., the income source of fishers is solely fishing or they have alternative/supplemental livelihood such as island hopping services, sari-sari store ownership, fish value adding and/or vending, souvenir selling, carpentry, as construction worker, farming and tour guiding) and their perceived benefit from CFT development in the island. From this dataset and using  = 0.05, is there a significant difference in estimated monthly income due to fisher type? How about due to the CFT perceived benefit? How about due to the interaction between fisher type and the perceived CFT benefit? a. Analyze manually and assume that the populations/groups are coming from normal distributions with constant variances. b. Analyze using SPSS. Start assigning numerical values to perceived CFT benefit and fisher type, and conduct the priori tests. Then, use the appropriate test statistic, and complete the analysis by doing posthoc, if necessary. c. If interaction is significant, add variables and assign values to each interaction and do posthoc to determine which interactions differ significantly. Then, discuss briefly the implication of the result of the statistical analysis. That is, considering the estimated monthly income of fishers and the findings from the data collected randomly from the fishers, do you think CFT can be used as a strategy to manage and utilize sustainably the fishery and aquatic resources in small islands like Guimaras

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

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The dataset below was collected from a survey to determine whether CFT development in the island can be used as a strategy for the sustainable management and utilization of the fishery and aquatic resources in small islands. It shows the monthly income (in thousand pesos) estimated by 200 randomly selected fishers in Guimaras according to the type of fishers (i.e., the income source of fishers is solely fishing or they have alternative/supplemental livelihood such as island hopping services, sari-sari store ownership, fish value adding and/or vending, souvenir selling, carpentry, as construction worker, farming and tour guiding) and their perceived benefit from CFT development in the island.

From this dataset and using  = 0.05, is there a significant difference in estimated monthly income due to
fisher type? How about due to the CFT perceived benefit? How about due to the interaction between fisher
type and the perceived CFT benefit?
a. Analyze manually and assume that the populations/groups are coming from normal distributions with
constant variances.
b. Analyze using SPSS. Start assigning numerical values to perceived CFT benefit and fisher type, and
conduct the priori tests. Then, use the appropriate test statistic, and complete the analysis by doing
posthoc, if necessary.
c. If interaction is significant, add variables and assign values to each interaction and do posthoc to determine
which interactions differ significantly. Then, discuss briefly the implication of the result of the statistical
analysis. That is, considering the estimated monthly income of fishers and the findings from the data collected randomly from the fishers, do you think CFT can be used as a strategy to manage and utilize
sustainably the fishery and aquatic resources in small islands like Guimaras?

Fisher Type
Fisher only
Fisher with
alternative
livelihood
Not benefited
3.00
5.00
7.00
6.00
2.50
10.00
10.00
18.00
6.00
5.00
14.20
3.00
7.00
6.00
5.00
7.00
21.00
15.00
10.00
4.00
5.00
12.00
15.00
6.00
10.00
7.00
4.00
10.00
10.00
4.00
2.50
3.50
3.50
8.00
6.00
5.50
2.20
3.00
3.00
6.50
3.00
3.50
5.00
5.00
13.00
3.00
1.30
5.00
8.00
5.00
Perceived CFT Benefit
Uncertain
15.00
8.00
4.00
2.00
8.00
4.50
3.00
6.00
3.00
4.00
7.20
2.50
2.00
5.50
3.00
4.00
5.00
10.00
30.00
3.00
5.00
12.00
6.00
5.00
25.02
14.50
8.00
3.50
6.00
5.00
31.05
4.00
6.00
7.50
10.50
1.50
6.00
1.00
15.00
15.00
8.00
15.00
3.00
5.00
6.00
51.00
3.80
4.00
6.00
5.00
2.50
10.00
8.00
9.60
3.00
6.00
8.00
3.00
4.00
12.00
5.00
5.00
6.45
6.00
7.50
7.50
3.50
10.00
12.00
10.00
6.00
6.00
6.00
4.00
4.00
3.00
3.00
5.00
Benefited
10.00
5.80
8.00
10.00
10.00
10.00
6.00
15.00
11.00
10.00
10.00
10.00
5.00
10.00
20.00
4.00
9.00
10.00
10.00
5.00
5.00
5.00
7.00
2.00
2.00
5.50
2.50
5.00
3.00
6.00
16.00
20.00
15.00
20.00
10.00
15.00
10.00
6.00
6.80
10.00
3.00
5.00
4.00
5.00
5.00
3.50
15.00
10.00
18.00
25.00
12.50
10.00
10.00
5.00
7.00
9.00
3.00
3.00
8.00
6.00
2.00
4.00
3.00
4.00
2.00
4.80
3.00
4.16
6.00
6.00
5.00
3.00

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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